Financial Premises

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Tuesday, August 30, 2016

Currently,
I have low financial liabilities and long term financial goals. So, I buy
stocks with the objective to hold them for long term horizon.

While identifying the stock
for investment, I focus on following parameter

Business – I look
for companies in flourishing sector. Then I select the companies with simple and
easy to understand business.

Companies - I prefer
the companies operating over long term in past. Thereby analyze its sustainable
competitive advantage (moat) and durability of that advantage. This is followed
by analyzing Company’s product portfolio to determine whether it commands
premium pricing?

Management – I look
for any increase or decrease in promoter stake in the company in recent years. I
prefer companies that are transparent and honesty in communication to
shareholders. I check whether the management is committed in its strategy. I
scan through annual reports to identify whether effective corporate governance
structure is in place. Management visions is analyzed by reading conference
call transcripts, Management Discussion and Analysis or interviews with leading
financial media.

Observing companies
product profile – I have inculcated that habit of observing the
products of the companies. When Patanjali products started getting greater shelf
spaces, I started tracking sale of FMCG gaints. I also compare company's
product with competitors and check customer's review on online shopping
websites as a part of stock analysis.

I have decided to invest portion of salary each month and
then spend the balance portion. I do not borrow to invest in equity

I study annual reports and other information about the
company from finance media to identify the next multi bagger stock.

I evaluate the stocks position by considering whether
the stock I am planning to buy or holding is affected by any of the behavioral
Bias like trend chasing, disposition effect, familiarity bias, Endowment or
other bias.

I have experienced that more I study about the company,
more I get biased about the stock. So, I have decided to make each investment
decision independent of previous decision.

Stock pick - Asian Paints

Asian Paints (AP) is in paints industry since 1945. AP business model is easy to understand.

Currently, it is a market leader in decorative paints, varnish and enamel with around 50% market share.

Its wide range of products (new product launches each year), geographies (customer in 65 countries) and wide distribution (30,000 dealers and 300 idea stores). AP is shifting from being only paints company to home décor company (adding modern kitchen space and bathroom fitting products). It has strong brand recallability.

Its promoter holding of 52.79% has been relatively constant. The management adheres to its core competency and have effectively integrated all mergers and acquisition. AP has effective corporate governance system in place.

AP has recorded 15.5% average annual revenue growth over 2007 - 2016 and average annual EBITDA growth of 19.2% during same period. It has consistently maintained Return on capital employed over 45% with positive free cash flow.

Saturday, July 23, 2016

Faircent is peer to peer lending platform. It acts as
marketplace and connect prospective borrowers and lenders. It is co-founded by
Rajat Gandhi and Vinay Mathews in 2014. Faircent provides small loans with average ticket size of around
Rs 1.5 lakh. It allows lenders to give personal loans in range of Rs 30,000 to
Rs 5 lakh and up to Rs 15 lakh for business purposes.

Business Model

Borrower
and lenders have to register on portal by submitting requisite details and
paying predetermined fees.

The
borrowers profile is analyzed based on its internal rating and score is
assigned to each borrowers. Based on the score the borrowers are bucketed into
different category.

Once
registered, borrowers and lenders can interact with each out without any
intermediate party. Borrowers can raise request on platform or reach out to
lenders citing their funds requirements. Lenders can also make offer to
borrowers.

Faircent
assigns ratings to borrowers by using algorithm that analyzes big data. The rating is based on demographic, financial
data from bank statements and credit cards, data from national credit bureau
indicating history of servicing loan and social data from facebook and LinkedIn
to identify the credit-worthiness of borrowers and to assign scores.

The
terms and conditions of lending, interest rate and installment phases are
negotiated and mutually decided by borrowers and lenders. The borrower has an
option to accept or reject the offers from the lenders.

Once
the consensus is reached, borrowers and lenders enter into formal contract. The
contracts specifies detail of financial transaction along with liabilities of
each party.

Pictorial representation based on publicly available information. Icon obtained from Board of Innovation

Innovation
based on psychology parameter: To ensure that borrowers do not default, the
Company creates connects borrowers and lenders from same profession or same
community or based on their mother tongue. This creates social pressure to
repay loan and thereby reduce incidences of default in repayment. The borrower's
profile is also rated by Editor - Low, Medium, High and very High risk. These
rating is displayed on website to all visitors.

TransUnion for real time credit appraisal of borrower. TransUnion has an eKYC module based on Aadhar card. The partnership will enable Faircent to build robust algorithm for data analytics and maps multiple data points of potential borrowers in real time.

Lenddo uses customers social data and online behavior information in its patented model to determine individual's willingness to pay.

Revenue Model

It’s a listing-based subscription model.

Listing fees from borrower - Rs. 1,500
Listing fees from lenders - Rs. 1,500 to invest up to Rs. 1.5
lakh. Thereafter, additional fees of Rs. 1,000 for every additional lakh. Thus,
the effective fees received by Faircent is 1% of the lending amount.

The
maximum recommended rate of interest ranges from 12% to 36% and the loan tenure
from 6 months to 36 months.

Borrower
of pay interest between 1-15th of every month. Failure to pay EMI attracts
penalty interest of 24% p.a. on the amount due for the duration of delay. This
penal interest is transferred to lender. Additionally, borrower also pays
towards administrative fees and other charges

The
interest received from borrowers is transferred to lender either by cheque or
online fund transfer.

If
borrowers defaults in paying regular monthly installment, then they are charged
penal interest which is directly given to lenders.

If
borrower profile is not accepted then Rs. 1,000 is refunded to them.

Funds Raised

So, if you have funds lying ideal, park it here and earn cherish passive income

LendingKart is an online financing company founded by Harshvardhan Lunia and Mukul Sachan. It provides working capital loan for short duration to small and medium enterprises.

It address the pain point of small businessman in traditional banking environment, where they has to undergo numerous evaluation process by bank before receiving funds.

Lending kart blends banking with technology to interpret data generated during online consumer activities. This big data is analyzed using analytics to determine its lending decision.

Business function

Online Application: SME Vendors wishing to avail loan can fill in online application form. Loans are provided in range of ₹50,000 to ₹1 crores without pledging of any of their assets as collateral for tenure ranging from 1 month to 1 year.

Low operating cost: Online business model enables lendingkart to keep its operational and distribution cost lower compare to branch model. Further, it operates from offices in Ahmedabad and Bangalore to cater to its customers base across 135 cities across 22 states as of Jun 2016.

Small employee base: Lendingkart provides loan without collateral, so there is no need for physical verification of collateral. Thereby, it can manage its routine operations with small employee base.

Technology partner: Lenddo's algorithm uses social media contacts and interactions of borrower and similar information to determine its credit worthiness. This collaboration with Lenddo will enable lendingkart to explore non-financial data for credit scoring evaluation.

Quick Evaluation Process: The repayment capacity of borrower is evaluated majorly focusing on vendor’s current year cash flows and business growth. Normally, loan is sanctioned in a day and disbursed within next 1-3 days.

Data Partner: Lendingkart has partnered with e-commerce marketplace website like flipkart, snapdeal, Jabong, Voonik, craftsvilla, CCavenue, PayU and paytm. It has also partnered with offline portal tradeindia. Partnering with these websites provides dual benefits to lendingkart.

Attract larger number of small business that are registered on e-commerce websites

Access e-commerce sellers quantative details like number of transactions carried out, annual turnover, cash flow and qualitative details like quality of its product, efficiency in responding to customers, ability to compete in markeplace.

It analyzes the credit worthiness of its borrowers based on approx 2,200 qualitative and quantitative parameters that it obtains from e-commerce platform, and thereby arrives at its lending decision.

Pictorial representation based on publicly available information. Icon obtained from Board of Innovation

Revenue Model

Lending cart charges interest of 1.5% - 2% per month to its borrowers, which is equivalent to interest rate of 18 - 24% per annum.

All loan are funds and sanctioned by LendingKart affiliate NBFCs.

Borrower pays one time processing charges of 1% of the sanctioned amount. Further, there are no pre-closure charges

Borrowers can pay interest or repay principal either biweekly or monthly

LendingKart witness 20% month-over-month growth in loan origination during 2014 - 2016. As per Techportal report Lendingkart disburses around 70 short term loans every month.

Funds raised

With the recent round of funding, the company has in total raised
Rs. 260 crore ($41 million) till date.